mqt.syrec 2.0.0

MQT SyReC Synthesizer: A Tool for HDL-based Synthesis of Reversible Circuits

[!NOTE] This project is currently in low maintenance mode. We will still fix bugs and accept pull requests, but we will not actively develop new features.

MQT SyReC Synthesizer - A Tool for HDL-based Synthesis of Reversible Circuits

MQT SyReC Synthesizer is a tool for HDL-based synthesis of reversible circuits. It is part of the Munich Quantum Toolkit (MQT).

Key Features

• Automatic synthesis of reversible circuits from high-level HDL: Accepts any HDL description following the SyReC grammar and syntax, enabling rapid prototyping and design of reversible logic.
• Two complementary synthesis schemes: Choose between cost-aware synthesis (minimizing gate cost) and line-aware synthesis (minimizing circuit lines), each with distinct trade-offs for resource optimization.
• Graphical User Interface (GUI): Intuitive GUI for specifying SyReC programs, visualizing circuits, and running synthesis, simulation, and cost analysis at the click of a button.
• Simulation and cost analysis: Simulate synthesized circuits and determine gate costs directly within the tool.
• Comprehensive SyReC language support: Implements the full SyReC language, including modules, parameterized bitwidths, multi-dimensional variables, and advanced assignment semantics (language reference).
• Python API and C++ core: High-performance C++ backend with Python bindings for integration into research and teaching workflows.
• Cross-platform and easy to install: Prebuilt Python wheels for Linux, macOS, and Windows via PyPI.

If you have any questions, feel free to create a discussion or an issue on GitHub.

Contributors and Supporters

The Munich Quantum Toolkit (MQT) is developed by the Chair for Design Automation at the Technical University of Munich and supported by the Munich Quantum Software Company (MQSC). Among others, it is part of the Munich Quantum Software Stack (MQSS) ecosystem, which is being developed as part of the Munich Quantum Valley (MQV) initiative.

Thank you to all the contributors who have helped make MQT SyReC Synthesizer a reality!

The MQT will remain free, open-source, and permissively licensed—now and in the future. We are firmly committed to keeping it open and actively maintained for the quantum computing community.

To support this endeavor, please consider:

• Starring and sharing our repositories: https://github.com/munich-quantum-toolkit
• Contributing code, documentation, tests, or examples via issues and pull requests
• Citing the MQT in your publications (see Cite This)
• Citing our research in your publications (see References)
• Using the MQT in research and teaching, and sharing feedback and use cases
• Sponsoring us on GitHub: https://github.com/sponsors/munich-quantum-toolkit

Getting Started

mqt.syrec is available via PyPI.

(.venv) $ pip install mqt.syrec

Once installed, start the GUI by running:

(.venv) $ syrec-editor

Detailed documentation and examples are available at ReadTheDocs.

System Requirements

Building the project requires a C++ compiler with support for C++20 and CMake 3.24 or newer. For details on how to build the project, please refer to the documentation. Building (and running) is continuously tested under Linux, macOS, and Windows using the latest available system versions for GitHub Actions. MQT SyReC Synthesizer is compatible with all officially supported Python versions.

Cite This

Please cite the work that best fits your use case.

MQT SyReC Synthesizer (the tool)

When citing the software itself or results produced with it, cite the MQT SyReC Synthesizer paper:

@article{adarsh2022syrecSynthesizer,
  title        = {{SyReC} {Synthesizer}: {An} {MQT} tool for synthesis of reversible circuits},
  author       = {Adarsh, Smaran and Burgholzer, Lukas and Manjunath, Tanmay and Wille, Robert},
  year         = {2022},
  journal      = {Software Impacts},
  publisher    = {Elsevier},
  url          = {https://doi.org/10.1016/j.simpa.2022.100451}
}

The Munich Quantum Toolkit (the project)

When discussing the overall MQT project or its ecosystem, cite the MQT Handbook:

@inproceedings{mqt,
  title        = {The {{MQT}} Handbook: {{A}} Summary of Design Automation Tools and Software for Quantum Computing},
  shorttitle   = {{The MQT Handbook}},
  author       = {Wille, Robert and Berent, Lucas and Forster, Tobias and Kunasaikaran, Jagatheesan and Mato, Kevin and Peham, Tom and Quetschlich, Nils and Rovara, Damian and Sander, Aaron and Schmid, Ludwig and Schoenberger, Daniel and Stade, Yannick and Burgholzer, Lukas},
  year         = 2024,
  booktitle    = {IEEE International Conference on Quantum Software (QSW)},
  doi          = {10.1109/QSW62656.2024.00013},
  eprint       = {2405.17543},
  eprinttype   = {arxiv},
  addendum     = {A live version of this document is available at \url{https://mqt.readthedocs.io}}
}

Peer-Reviewed Research

When citing the underlying methods and research, please reference the most relevant peer-reviewed publications from the list below:

[1] S. Adarsh, L. Burgholzer, T. Manjunath, and R. Wille. SyReC Synthesizer: An MQT tool for synthesis of reversible circuits. Software Impacts, 2022.

[2] R. Wille, S. Offermann, and R. Drechsler. SyReC: A Programming Language for Synthesis of Reversible Circuits. Forum on Specification and Design Languages (FDL), 2010.

[3] R. Wille, E. Schönborn, M. Soeken, and R. Drechsler. SyReC: A hardware description language for the specification and synthesis of reversible circuits. Integration (The VLSI Journal), 2016.

[4] R. Wille, M. Haghparast, S. Adarsh, and T. Manjunath. Towards HDL-based Synthesis of Reversible Circuits with No Additional Lines. International Conference on Computer Aided Design (ICCAD), 2019.

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Acknowledgements

The Munich Quantum Toolkit has been supported by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (grant agreement No. 101001318), the Bavarian State Ministry for Science and Arts through the Distinguished Professorship Program, as well as the Munich Quantum Valley, which is supported by the Bavarian state government with funds from the Hightech Agenda Bayern Plus.